{"total":130,"rows":[{"id":"2506.08009","title":"Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion","created":"2025-06-09","cited_by_count":625,"area":"diffusion"},{"id":"2509.25161","title":"Rolling Forcing: Autoregressive Long Video Diffusion in Real Time","created":"2025-09-29","cited_by_count":234,"area":"wm"},{"id":"2509.26645","title":"TTT3R: 3D Reconstruction as Test-Time Training","created":"2025-09-30","cited_by_count":129,"area":null},{"id":"2512.04040","title":"RELIC: Interactive Video World Model with Long-Horizon Memory","created":"2025-12-03","cited_by_count":96,"area":"wm"},{"id":"2508.21058","title":"Mixture of Contexts for Long Video Generation","created":"2025-08-28","cited_by_count":95,"area":null},{"id":"2507.06203","title":"A Survey on Latent Reasoning","created":"2025-07-08","cited_by_count":81,"area":"lr"},{"id":"2511.01266","title":"MotionStream: Real-Time Video Generation with Interactive Motion Controls","created":"2025-11-03","cited_by_count":76,"area":null},{"id":"2512.23675","title":"End-to-End Test-Time Training for Long Context","created":"2025-12-29","cited_by_count":62,"area":null},{"id":"2512.15702","title":"End-to-End Training for Autoregressive Video Diffusion via Self-Resampling","created":"2025-12-17","cited_by_count":52,"area":"diffusion"},{"id":"2512.14699","title":"MemFlow: Flowing Adaptive Memory for Consistent and Efficient Long Video Narratives","created":"2025-12-16","cited_by_count":45,"area":null},{"id":"2604.13036","title":"Lyra 2.0: Explorable Generative 3D Worlds","created":"2026-04-14","cited_by_count":44,"area":null},{"id":"2508.15884","title":"Jet-Nemotron: Efficient Language Model with Post Neural Architecture Search","created":"2025-08-21","cited_by_count":41,"area":null},{"id":"2603.03269","title":"LoGeR: Long-Context Geometric Reconstruction with Hybrid Memory","created":"2026-03-03","cited_by_count":39,"area":null},{"id":"2602.07775","title":"Rolling Sink: Bridging Limited-Horizon Training and Open-Ended Testing in Autoregressive Video Diffusion","created":"2026-02-08","cited_by_count":32,"area":"diffusion"},{"id":"2604.08542","title":"Scal3R: Scalable Test-Time Training for Large-Scale 3D Reconstruction","created":"2026-04-09","cited_by_count":31,"area":null},{"id":"2605.18739","title":"LongLive-2.0: An NVFP4 Parallel Infrastructure for Long Video Generation","created":"2026-05-18","cited_by_count":30,"area":"diffusion"},{"id":"2603.04385","title":"ZipMap: Linear-Time Stateful 3D Reconstruction via Test-Time Training","created":"2026-03-04","cited_by_count":26,"area":null},{"id":"2604.07209","title":"INSPATIO-WORLD: A Real-Time 4D World Simulator via Spatiotemporal Autoregressive Modeling","created":"2026-04-08","cited_by_count":21,"area":"wm"},{"id":"2604.06169","title":"In-Place Test-Time Training","created":"2026-04-07","cited_by_count":20,"area":null},{"id":"2607.15275","title":"RoboTTT: Context Scaling for Robot Policies","created":"2026-07-16","cited_by_count":19,"area":null},{"id":"2510.18775","title":"UltraGen: High-Resolution Video Generation with Hierarchical Attention","created":"2025-10-21","cited_by_count":18,"area":null},{"id":"2512.01643","title":"ViT$^3$: Unlocking Test-Time Training in Vision","created":"2025-12-01","cited_by_count":18,"area":null},{"id":"2602.23361","title":"VGG-T$^3$: Offline Feed-Forward 3D Reconstruction at Scale","created":"2026-02-26","cited_by_count":18,"area":null},{"id":"2603.09488","title":"Streaming Autoregressive Video Generation via Diagonal Distillation","created":"2026-03-10","cited_by_count":18,"area":"diffusion"},{"id":"2602.01077","title":"PISA: Piecewise Sparse Attention Is Wiser for Efficient Diffusion Transformers","created":"2026-02-01","cited_by_count":17,"area":"diffusion"},{"id":"2512.12080","title":"BAgger: Backwards Aggregation for Mitigating Drift in Autoregressive Video Diffusion Models","created":"2025-12-12","cited_by_count":16,"area":"wm"},{"id":"2602.03747","title":"LIVE: Long-horizon Interactive Video World Modeling","created":"2026-02-03","cited_by_count":16,"area":"wm"},{"id":"2603.06679","title":"MultiGen: Level-Design for Editable Multiplayer Worlds in Diffusion Game Engines","created":"2026-03-03","cited_by_count":16,"area":"wm"},{"id":"2602.14941","title":"AnchorWeave: World-Consistent Video Generation with Retrieved Local Spatial Memories","created":"2026-02-16","cited_by_count":15,"area":null},{"id":"2602.24281","title":"Memory Caching: RNNs with Growing Memory","created":"2026-02-27","cited_by_count":15,"area":null},{"id":"2603.08703","title":"HiAR: Efficient Autoregressive Long Video Generation via Hierarchical Denoising","created":"2026-03-09","cited_by_count":15,"area":null},{"id":"2604.15239","title":"TokenGS: Decoupling 3D Gaussian Prediction from Pixels with Learnable Tokens","created":"2026-04-16","cited_by_count":15,"area":null},{"id":"2506.18890","title":"4D-LRM: Large Space-Time Reconstruction Model From and To Any View at Any Time","created":"2025-06-23","cited_by_count":14,"area":null},{"id":"2507.16577","title":"Scaling Linear Attention with Sparse State Expansion","created":"2025-07-22","cited_by_count":13,"area":null},{"id":"2602.21204","title":"Test-Time Training with KV Binding Is Secretly Linear Attention","created":"2026-02-24","cited_by_count":13,"area":null},{"id":"2606.20562","title":"MemoryWAM: Efficient World Action Modeling with Persistent Memory","created":"2026-06-18","cited_by_count":13,"area":"wm"},{"id":"2602.20160","title":"tttLRM: Test-Time Training for Long Context and Autoregressive 3D Reconstruction","created":"2026-02-23","cited_by_count":12,"area":null},{"id":"2602.24289","title":"Mode Seeking meets Mean Seeking for Fast Long Video Generation","created":"2026-02-27","cited_by_count":12,"area":"diffusion"},{"id":"2603.12255","title":"Spatial-TTT: Streaming Visual-based Spatial Intelligence with Test-Time Training","created":"2026-03-12","cited_by_count":11,"area":null},{"id":"2604.21221","title":"Sparse Forcing: Native Trainable Sparse Attention for Real-time Autoregressive Diffusion Video Generation","created":"2026-04-23","cited_by_count":11,"area":"diffusion"},{"id":"2510.04786","title":"Learning on the Job: Test-Time Curricula for Targeted Reinforcement Learning","created":"2025-10-06","cited_by_count":9,"area":"deeprl"},{"id":"2602.21341","title":"Scaling View Synthesis Transformers","created":"2026-02-24","cited_by_count":9,"area":null},{"id":"2603.13875","title":"GradMem: Learning to Write Context into Memory with Test-Time Gradient Descent","created":"2026-03-14","cited_by_count":9,"area":null},{"id":"2511.07343","title":"TNT: Improving Chunkwise Training for Test-Time Memorization","created":"2025-11-10","cited_by_count":8,"area":null},{"id":"2512.05354","title":"SplatPainter: Interactive Authoring of 3D Gaussians from 2D Edits via Test-Time Training","created":"2025-12-05","cited_by_count":7,"area":null},{"id":"2512.07806","title":"Multi-view Pyramid Transformer: Look Coarser to See Broader","created":"2025-12-08","cited_by_count":7,"area":null},{"id":"2601.19895","title":"Post-LayerNorm Is Back: Stable, ExpressivE, and Deep","created":"2026-01-27","cited_by_count":7,"area":null},{"id":"2512.19678","title":"WorldWarp: Propagating 3D Geometry with Asynchronous Video Diffusion","created":"2025-12-22","cited_by_count":6,"area":"diffusion"},{"id":"2604.07279","title":"Mem3R: Streaming 3D Reconstruction with Hybrid Memory via Test-Time Training","created":"2026-04-08","cited_by_count":6,"area":null},{"id":"2606.01774","title":"FLARE: Diffusion for Hybrid Language Model","created":"2026-06-01","cited_by_count":6,"area":null},{"id":"2606.09803","title":"Echo-Memory: A Controlled Study of Memory in Action World Models","created":"2026-06-08","cited_by_count":6,"area":"wm"},{"id":"2607.25357","title":"Raven: High-Recall Sequence Modeling with Sparse Memory Routing","created":"2026-07-28","cited_by_count":6,"area":null},{"id":"2506.01153","title":"Weight-Space Linear Recurrent Neural Networks","created":"2025-06-01","cited_by_count":5,"area":null},{"id":"2509.24510","title":"Specialization after Generalization: Towards Understanding Test-Time Training in Foundation Models","created":"2025-09-29","cited_by_count":5,"area":null},{"id":"2512.06802","title":"VDOT: Efficient Unified Video Creation via Optimal Transport Distillation","created":"2025-12-07","cited_by_count":5,"area":null},{"id":"2603.28489","title":"Video Generation Models as World Models: Efficient Paradigms, Architectures and Algorithms","created":"2026-03-30","cited_by_count":5,"area":"wm"},{"id":"2605.15824","title":"FashionChameleon: Towards Real-Time and Interactive Human-Garment Video Customization","created":"2026-05-15","cited_by_count":5,"area":null},{"id":"2606.04536","title":"Scaling Self-Evolving Agents via Parametric Memory","created":"2026-06-03","cited_by_count":5,"area":"agents"},{"id":"2608.13416","title":"StreamTTT: Reconciling Real-Time Perception and Long-Term Memory in Streaming VLMs","created":"2026-08-13","cited_by_count":5,"area":null},{"id":"2608.26794","title":"Ring Forcing: Towards Precise Long-Term Memory for Autoregressive Video Diffusion","created":"2026-08-27","cited_by_count":5,"area":"diffusion"},{"id":"2510.24718","title":"Generative View Stitching","created":"2025-10-28","cited_by_count":4,"area":"diffusion"},{"id":"2512.10267","title":"Long-LRM++: Preserving Fine Details in Feed-Forward Wide-Coverage Reconstruction","created":"2025-12-11","cited_by_count":4,"area":null},{"id":"2601.14959","title":"Towards Holistic Modeling for Video Frame Interpolation with Auto-regressive Diffusion Transformers","created":"2026-01-21","cited_by_count":4,"area":"diffusion"},{"id":"2602.10095","title":"Causality in Video Diffusers is Separable from Denoising","created":"2026-02-10","cited_by_count":4,"area":null},{"id":"2604.01170","title":"Online Reasoning Calibration: Test-Time Training Enables Generalizable Conformal LLM Reasoning","created":"2026-04-01","cited_by_count":4,"area":"lr"},{"id":"2605.05838","title":"MDN: Parallelizing Stepwise Momentum for Delta Linear Attention","created":"2026-05-07","cited_by_count":4,"area":null},{"id":"2509.25741","title":"Test time training enhances in-context learning of nonlinear functions","created":"2025-09-30","cited_by_count":3,"area":null},{"id":"2512.03040","title":"Video4Spatial: Towards Visuospatial Intelligence with Context-Guided Video Generation","created":"2025-12-02","cited_by_count":3,"area":null},{"id":"2601.16296","title":"Memory-V2V: Memory-Augmented Video-to-Video Diffusion for Consistent Multi-Turn Editing","created":"2026-01-22","cited_by_count":3,"area":"diffusion"},{"id":"2604.07350","title":"Fast Spatial Memory with Elastic Test-Time Training","created":"2026-04-08","cited_by_count":3,"area":null},{"id":"2605.02772","title":"Linearizing Vision Transformer with Test-Time Training","created":"2026-05-04","cited_by_count":3,"area":null},{"id":"2605.17478","title":"Mamba-VGGT: Persistent Long-Sequence Video Geometry Grounded Transformer via External Sliding Window Mamba Memory","created":"2026-05-17","cited_by_count":3,"area":"ssm"},{"id":"2605.30349","title":"AdaState: Self-Evolving Anchors for Streaming Video Generation","created":"2026-05-28","cited_by_count":3,"area":"diffusion"},{"id":"2606.24893","title":"AgentOdyssey: Open-Ended Long-Horizon Text Game Generation for Test-Time Continual Learning Agents","created":"2026-05-29","cited_by_count":3,"area":null},{"id":"2608.07110","title":"Modular TTT: Rethinking Test-Time Training as Composable Modules","created":"2026-08-07","cited_by_count":3,"area":null},{"id":"2511.19437","title":"LumiTex: Towards High-Fidelity PBR Texture Generation with Illumination Context","created":"2025-11-24","cited_by_count":2,"area":null},{"id":"2602.13680","title":"AllMem: A Memory-centric Recipe for Efficient Long-context Modeling","created":"2026-02-14","cited_by_count":2,"area":null},{"id":"2604.05182","title":"LSRM: High-Fidelity Object-Centric Reconstruction via Scaled Context Windows","created":"2026-04-06","cited_by_count":2,"area":null},{"id":"2605.20708","title":"Rethinking Cross-Layer Information Routing in Diffusion Transformers","created":"2026-05-20","cited_by_count":2,"area":"diffusion"},{"id":"2605.29891","title":"DVSM: Decoder-only View Synthesis Model Done Right","created":"2026-05-28","cited_by_count":2,"area":null},{"id":"2606.02775","title":"AURA: Action-Gated Memory for Robot Policies at Constant VRAM","created":"2026-06-01","cited_by_count":2,"area":"inference"},{"id":"2608.01672","title":"Learning What to Remember: Test-Time Training via Context Distillation","created":"2026-08-03","cited_by_count":2,"area":null},{"id":"2608.30692","title":"Can Video World Models Track Unobserved World States?","created":"2026-08-31","cited_by_count":2,"area":"wm"},{"id":"2602.16704","title":"Reinforced Fast Weights with Next-Sequence Prediction","created":"2026-02-18","cited_by_count":1,"area":null},{"id":"2603.06642","title":"SR-TTT Does Not Learn Retrieval: A Correction and Mechanistic Post-Mortem of Surprisal-Aware Residual Test-Time Training","created":"2026-02-26","cited_by_count":1,"area":"inference"},{"id":"2603.09221","title":"Beyond Test-Time Memory: State-Space Optimal Control for LLM Reasoning","created":"2026-03-10","cited_by_count":1,"area":"lr"},{"id":"2605.06270","title":"Spark3R: Asymmetric Token Reduction Makes Fast Feed-Forward 3D Reconstruction","created":"2026-05-07","cited_by_count":1,"area":"inference"},{"id":"2605.09877","title":"Key-Value Means: Transformers with Expandable Block-Recurrent Compressed Memory","created":"2026-05-11","cited_by_count":1,"area":null},{"id":"2606.25342","title":"Lifelong In-Context Learning with Transformers Requires Parametric Forms of Attention","created":"2026-06-24","cited_by_count":1,"area":null},{"id":"2607.00368","title":"Beyond Perplexity: A Behavioral Evaluation Framework for Deployment-Memory Claims in LLM Test-Time Training","created":"2026-07-01","cited_by_count":1,"area":null},{"id":"2607.02711","title":"RayTun3R: Online Camera Adaptation in 3D Foundation Models","created":"2026-07-02","cited_by_count":1,"area":null},{"id":"2607.05376","title":"MV-Forcing: Long Multi-View Video Generation via 4D-Grounded Spatio-Temporal Self-Forcing","created":"2026-07-06","cited_by_count":1,"area":"diffusion"},{"id":"2607.07168","title":"NoDrift3R: Raymap-Guided Coupling for Drift-Robust Unposed Feed-Forward 3D Reconstruction","created":"2026-07-08","cited_by_count":1,"area":"wm"},{"id":"2607.09415","title":"Self-Guided Test-Time Training for Long-Context LLMs","created":"2026-07-10","cited_by_count":1,"area":null},{"id":"2608.16844","title":"Proteus: Incremental Memory Activation for Long-Context Sequence Modeling","created":"2026-08-17","cited_by_count":1,"area":null},{"id":"2608.21308","title":"Rethinking Expressivity and Efficiency in Test-Time Training","created":"2026-08-21","cited_by_count":1,"area":"lr"},{"id":"2610.12002","title":"Agentic-TTT: Training test-time policy for test-time training","created":"2026-10-08","cited_by_count":1,"area":"agents"},{"id":"2508.08289","title":"Attention as Conditioning: What Classical Learning Theory Predicts About Linear Transformers","created":"2025-08-05","cited_by_count":0,"area":null},{"id":"2508.11921","title":"ENA: Efficient N-dimensional Attention","created":"2025-08-16","cited_by_count":0,"area":null},{"id":"2602.10796","title":"PRISM: Parallel Residual Iterative Sequence Model","created":"2026-02-11","cited_by_count":0,"area":null}],"next_cursor":"100"}